{
 "metadata": {
  "signature": "sha256:fdfee831dd0daaef575995a826750485a175113107863a079d6f98007e943ce8"
 },
 "nbformat": 3,
 "nbformat_minor": 0,
 "worksheets": [
  {
   "cells": [
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Finding the Convex Hull of a 2-D Dataset\n",
      "========================================\n",
      "\n",
      "> **NOTE**: you may want to use use [scipy.spatial.ConvexHull](http://docs.scipy.org/doc/scipy/reference/generated/scipy.spatial.ConvexHull.html) instead of this.\n",
      "\n",
      "This code finds the subsets of points describing the convex hull around\n",
      "a set of 2-D data points. The code optionally uses pylab to animate its\n",
      "progress."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import numpy as n, pylab as p, time\n",
      "\n",
      "def _angle_to_point(point, centre):\n",
      "    '''calculate angle in 2-D between points and x axis'''\n",
      "    delta = point - centre\n",
      "    res = n.arctan(delta[1] / delta[0])\n",
      "    if delta[0] < 0:\n",
      "        res += n.pi\n",
      "    return res\n",
      "\n",
      "\n",
      "def _draw_triangle(p1, p2, p3, **kwargs):\n",
      "    tmp = n.vstack((p1,p2,p3))\n",
      "    x,y = [x[0] for x in zip(tmp.transpose())]\n",
      "    p.fill(x,y, **kwargs)\n",
      "    #time.sleep(0.2)\n",
      "\n",
      "\n",
      "def area_of_triangle(p1, p2, p3):\n",
      "    '''calculate area of any triangle given co-ordinates of the corners'''\n",
      "    return n.linalg.norm(n.cross((p2 - p1), (p3 - p1)))/2.\n",
      "\n",
      "\n",
      "def convex_hull(points, graphic=True, smidgen=0.0075):\n",
      "    '''Calculate subset of points that make a convex hull around points\n",
      "\n",
      "Recursively eliminates points that lie inside two neighbouring points until only convex hull is remaining.\n",
      "\n",
      ":Parameters:\n",
      "    points : ndarray (2 x m)\n",
      "        array of points for which to find hull\n",
      "    graphic : bool\n",
      "        use pylab to show progress?\n",
      "    smidgen : float\n",
      "        offset for graphic number labels - useful values depend on your data range\n",
      "\n",
      ":Returns:\n",
      "    hull_points : ndarray (2 x n)\n",
      "        convex hull surrounding points\n",
      "'''\n",
      "    if graphic:\n",
      "        p.clf()\n",
      "        p.plot(points[0], points[1], 'ro')\n",
      "    n_pts = points.shape[1]\n",
      "    assert(n_pts > 5)\n",
      "    centre = points.mean(1)\n",
      "    if graphic: p.plot((centre[0],),(centre[1],),'bo')\n",
      "    angles = n.apply_along_axis(_angle_to_point, 0, points, centre)\n",
      "    pts_ord = points[:,angles.argsort()]\n",
      "    if graphic:\n",
      "        for i in xrange(n_pts):\n",
      "            p.text(pts_ord[0,i] + smidgen, pts_ord[1,i] + smidgen, \\\n",
      "                   '%d' % i)\n",
      "    pts = [x[0] for x in zip(pts_ord.transpose())]\n",
      "    prev_pts = len(pts) + 1\n",
      "    k = 0\n",
      "    while prev_pts > n_pts:\n",
      "        prev_pts = n_pts\n",
      "        n_pts = len(pts)\n",
      "        if graphic: p.gca().patches = []\n",
      "        i = -2\n",
      "        while i < (n_pts - 2):\n",
      "            Aij = area_of_triangle(centre, pts[i],     pts[(i + 1) % n_pts])\n",
      "            Ajk = area_of_triangle(centre, pts[(i + 1) % n_pts], \\\n",
      "                                   pts[(i + 2) % n_pts])\n",
      "            Aik = area_of_triangle(centre, pts[i],     pts[(i + 2) % n_pts])\n",
      "            if graphic:\n",
      "                _draw_triangle(centre, pts[i], pts[(i + 1) % n_pts], \\\n",
      "                               facecolor='blue', alpha = 0.2)\n",
      "                _draw_triangle(centre, pts[(i + 1) % n_pts], \\\n",
      "                               pts[(i + 2) % n_pts], \\\n",
      "                               facecolor='green', alpha = 0.2)\n",
      "                _draw_triangle(centre, pts[i], pts[(i + 2) % n_pts], \\\n",
      "                               facecolor='red', alpha = 0.2)\n",
      "            if Aij + Ajk < Aik:\n",
      "                if graphic: p.plot((pts[i + 1][0],),(pts[i + 1][1],),'go')\n",
      "                del pts[i+1]\n",
      "            i += 1\n",
      "            n_pts = len(pts)\n",
      "        k += 1\n",
      "    return n.asarray(pts)\n",
      "\n",
      "if __name__ == \"__main__\":\n",
      "    points = n.random.random_sample((2,40))\n",
      "    hull_pts = convex_hull(points)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": "iVBORw0KGgoAAAANSUhEUgAAAWgAAAEECAYAAAAF0670AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nR1ImXlHSSwAAAABJRU5ErkJggg==\n",
       "text": [
        "<matplotlib.figure.Figure at 0x7f884f7a8690>"
       ]
      }
     ],
     "prompt_number": 2
    }
   ],
   "metadata": {}
  }
 ]
}